Carey E. Priebe

According to our database1, Carey E. Priebe authored at least 161 papers between 1988 and 2022.

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Bibliography

2022
Entrywise Estimation of Singular Vectors of Low-Rank Matrices With Heteroskedasticity and Dependence.
IEEE Trans. Inf. Theory, 2022

Deep Learning with Label Noise: A Hierarchical Approach.
CoRR, 2022

ART-SS: An Adaptive Rejection Technique for Semi-Supervised restoration for adverse weather-affected images.
CoRR, 2022

Mental State Classification Using Multi-graph Features.
CoRR, 2022

Prospective Learning: Back to the Future.
CoRR, 2022

Multiplex graph matching matched filters.
Appl. Netw. Sci., 2022

2021
Graph Matching Between Bipartite and Unipartite Networks: To Collapse, or Not to Collapse, That Is the Question.
IEEE Trans. Netw. Sci. Eng., 2021

Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics.
PLoS Comput. Biol., 2021

Joint Embedding of Graphs.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings.
J. Mach. Learn. Res., 2021

Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace.
J. Mach. Learn. Res., 2021

Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering.
J. Comput. Graph. Stat., 2021

Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks.
J. Comput. Graph. Stat., 2021

Graph Matching via Optimal Transport.
CoRR, 2021

Towards a theory of out-of-distribution learning.
CoRR, 2021

Graph Encoder Embedding.
CoRR, 2021

A principled (and practical) test for network comparison.
CoRR, 2021

Leveraging semantically similar queries for ranking via combining representations.
CoRR, 2021

Dynamic Silos: Modularity in intra-organizational communication networks before and during the Covid-19 pandemic.
CoRR, 2021

Beyond the adjacency matrix: random line graphs and inference for networks with edge attributes.
CoRR, 2021

Inducing a hierarchy for multi-class classification problems.
CoRR, 2021

Subgraph nomination: Query by Example Subgraph Retrieval in Networks.
CoRR, 2021

The phantom alignment strength conjecture: practical use of graph matching alignment strength to indicate a meaningful graph match.
Appl. Netw. Sci., 2021

An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020
Sparse Representation Classification Beyond ℓ1 Minimization and the Subspace Assumption.
IEEE Trans. Inf. Theory, 2020

Vertex nomination via seeded graph matching.
Stat. Anal. Data Min., 2020

Matched Filters for Noisy Induced Subgraph Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Variability and heritability of mouse brain structure: Microscopic MRI atlases and connectomes for diverse strains.
NeuroImage, 2020

Sparse Projection Oblique Randomer Forests.
J. Mach. Learn. Res., 2020

Vertex nomination: The canonical sampling and the extended spectral nomination schemes.
Comput. Stat. Data Anal., 2020

A partition-based similarity for classification distributions.
CoRR, 2020

Vertex nomination between graphs via spectral embedding and quadratic programming.
CoRR, 2020

A Simple Spectral Failure Mode for Graph Convolutional Networks.
CoRR, 2020

On identifying unobserved heterogeneity in stochastic blockmodel graphs with vertex covariates.
CoRR, 2020

Learning to rank via combining representations.
CoRR, 2020

On the role of features in vertex nomination: Content and context together are better (sometimes).
CoRR, 2020

A general approach to progressive intelligence.
CoRR, 2020

Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs.
CoRR, 2020

Geodesic Forests.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Connectome Smoothing via Low-Rank Approximations.
IEEE Trans. Medical Imaging, 2019

Alignment strength and correlation for graphs.
Pattern Recognit. Lett., 2019

Seeded graph matching.
Pattern Recognit., 2019

On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs.
Netw. Sci., 2019

On Consistent Vertex Nomination Schemes.
J. Mach. Learn. Res., 2019

The Exact Equivalence of Independence Testing and Two-Sample Testing.
CoRR, 2019

Spectral clustering in the weighted stochastic block model.
CoRR, 2019

Graphyti: A Semi-External Memory Graph Library for FlashGraph.
CoRR, 2019

Geodesic Learning via Unsupervised Decision Forests.
CoRR, 2019

Vertex Classification on Weighted Networks.
CoRR, 2019

Sparse Representation Classification via Screening for Graphs.
CoRR, 2019

Vertex Nomination, Consistent Estimation, and Adversarial Modification.
CoRR, 2019

clusterNOR: A NUMA-Optimized Clustering Framework.
CoRR, 2019

Multiplex graph matching matched filters.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
On a 'Two Truths' Phenomenon in Spectral Graph Clustering.
CoRR, 2018

FlashR: parallelize and scale R for machine learning using SSDs.
Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

Out-of-sample extension of graph adjacency spectral embedding.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs.
IEEE Trans. Parallel Distributed Syst., 2017

Community Detection and Classification in Hierarchical Stochastic Blockmodels.
IEEE Trans. Netw. Sci. Eng., 2017

Manifold matching using shortest-path distance and joint neighborhood selection.
Pattern Recognit. Lett., 2017

Statistical Inference on Random Dot Product Graphs: a Survey.
J. Mach. Learn. Res., 2017

A statistical interpretation of spectral embedding: the generalised random dot product graph.
CoRR, 2017

Joint Embedding of Graphs.
CoRR, 2017

Statistical inference for network samples using subgraph counts.
CoRR, 2017

A Central Limit Theorem for an Omnibus Embedding of Multiple Random Dot Product Graphs.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library.
Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing, 2017

2016
Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands.
Remote. Sens., 2016

Graph Matching: Relax at Your Own Risk.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

A Model Selection Approach for Clustering a Multinomial Sequence with Non-Negative Factorization.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Robust Vertex Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching.
J. Mach. Learn. Res., 2016

FlashMatrix: Parallel, Scalable Data Analysis with Generalized Matrix Operations using Commodity SSDs.
CoRR, 2016

Semi-External Memory Sparse Matrix Multiplication on Billion-node Graphs in a Multicore Architecture.
CoRR, 2016

An SSD-based eigensolver for spectral analysis on billion-node graphs.
CoRR, 2016

NUMA-optimized In-memory and Semi-external-memory Parameterized Clustering.
CoRR, 2016

Cross-Domain Entity Resolution in Social Media.
CoRR, 2016

On the Incommensurability Phenomenon.
J. Classif., 2016

Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities.
J. Classif., 2016

2015
Spectral clustering for divide-and-conquer graph matching.
Parallel Comput., 2015

An integrative framework for sensor-based measurement of teamwork in healthcare.
J. Am. Medical Informatics Assoc., 2015

A penalty search algorithm for the obstacle neutralization problem.
Comput. Oper. Res., 2015

Shuffled Graph Classification: Theory and Connectome Applications.
J. Classif., 2015

FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs.
Proceedings of the 13th USENIX Conference on File and Storage Technologies, 2015

2014
Locality Statistics for Anomaly Detection in Time Series of Graphs.
IEEE Trans. Signal Process., 2014

Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Generalized canonical correlation analysis for classification.
J. Multivar. Anal., 2014

Seeded graph matching for correlated Erdös-Rényi graphs.
J. Mach. Learn. Res., 2014

An Automated Images-to-Graphs Framework for High Resolution Connectomics.
Frontiers Neuroinformatics, 2014

Active Community Detection in Massive Graphs.
CoRR, 2014

An Automated Images-to-Graphs Pipeline for High Resolution Connectomics.
CoRR, 2014

2013
Attribute Fusion in a Latent Process Model for Time Series of Graphs.
IEEE Trans. Signal Process., 2013

Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown.
SIAM J. Matrix Anal. Appl., 2013

Generalized canonical correlation analysis for disparate data fusion.
Pattern Recognit. Lett., 2013

Efficiency investigation of manifold matching for text document classification.
Pattern Recognit. Lett., 2013

Graph Classification Using Signal-Subgraphs: Applications in Statistical Connectomics.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

On Latent Position Inference from Doubly Stochastic Messaging Activities.
Multiscale Model. Simul., 2013

Anomaly Detection in Time Series of Graphs using Fusion of Graph Invariants.
IEEE J. Sel. Top. Signal Process., 2013

Metric Space Structures for Computational Anatomy.
Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013

Inference in time series of graphs using locality statistics.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Computing scalable multivariate glocal invariants of large (brain-) graphs.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

2012
Quantitative Horizon Scanning for Mitigating Technological Surprise: Detecting the Potential for Collaboration at the Interface.
Stat. Anal. Data Min., 2012

Fusion and inference from multiple data sources in a commensurate space.
Stat. Anal. Data Min., 2012

Vertex Nomination via Content and Context
CoRR, 2012

A bootstrap interval estimator for Bayes' classification error.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

A Comparison of Graph Embedding Methods for Vertex Nomination.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2011
The Effect of Model Misspecification on Semi-Supervised Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

Sensor information monotonicity in disambiguation protocols.
J. Oper. Res. Soc., 2011

Fast Inexact Graph Matching with Applications in Statistical Connectomics
CoRR, 2011

Anomaly detection for random graphs using distributions of vertex invariants.
Proceedings of the 45st Annual Conference on Information Sciences and Systems, 2011

2010
Efficient, optimal stochastic-action selection when limited by an action budget.
Math. Methods Oper. Res., 2010

A Graph-Search Based Navigation Algorithm for Traversing A Potentially Hazardous Area with Disambiguation.
Int. J. Oper. Res. Inf. Syst., 2010

Statistical inference on attributed random graphs: Fusion of graph features and content: An experiment on time series of Enron graphs.
Comput. Stat. Data Anal., 2010

Statistical inference on attributed random graphs: Fusion of graph features and content.
Comput. Stat. Data Anal., 2010

Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices.
J. Classif., 2010

Random attributed graphs for statistical inference from content and context.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
On the monotone likelihood ratio property for the convolution of independent binomial random variables.
Discret. Appl. Math., 2009

Statistical Analysis of Hippocampus Shape Using a Modified Mann-Whitney-Wilcoxon Test.
Proceedings of the Bio-Science and Bio-Technology, 2009

2008
On the anomalous behaviour of a class of locality statistics.
Discret. Math., 2008

Iterative Denoising.
Comput. Stat., 2008

Semisupervised learning from dissimilarity data.
Comput. Stat. Data Anal., 2008

The out-of-sample problem for classical multidimensional scaling.
Comput. Stat. Data Anal., 2008

Predicting unobserved links in incompletely observed networks.
Comput. Stat. Data Anal., 2008

Computation of Csiszár's mutual Information of order α.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

2007
Disambiguation Protocols Based on Risk Simulation.
IEEE Trans. Syst. Man Cybern. Part A, 2007

A data-adaptive methodology for finding an optimal weighted generalized Mann-Whitney-Wilcoxon statistic.
Comput. Stat. Data Anal., 2007

Cross-Instance Tuning of Unsupervised Document Clustering Algorithms.
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2007

Iterative Denoising using Jensen-Renyi Divergences with an Application to Unsupervised Document Categorization.
Proceedings of the IEEE International Conference on Acoustics, 2007

Hippocampus Shape-Space Analysis of Clinically Depressed, High Risk, and Control Populations.
Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies 2007, 2007

Validation of Alternating Kernel Mixture Method Based Segmentation of the Human Brain.
Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies 2007, 2007

2006
On the distribution of the domination number of a new family of parametrized random digraphs.
Model. Assist. Stat. Appl., 2006

A new family of proximity graphs: Class cover catch digraphs.
Discret. Appl. Math., 2006

Segmenting magnetic resonance images via hierarchical mixture modelling.
Comput. Stat. Data Anal., 2006

Relative density of the random r.
Comput. Stat. Data Anal., 2006

2005
Scan Statistics on Enron Graphs.
Comput. Math. Organ. Theory, 2005

A Hierarchical Methodology for Class Detection Problems with Skewed Priors.
J. Classif., 2005

Unsupervised classification via decision trees: an information-theoretic perspective.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Biomedical Informatics Research Network: Integrating Multi-Site Neuroimaging Data Acquisition, Data Sharing and Brain Morphometric Processing.
Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems (CBMS 2005), 2005

2004
The generalized spherical homeomorphism theorem for digital images.
IEEE Trans. Medical Imaging, 2004

Integrated Sensing and Processing Decision Trees.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

2003
Characterizing the scale dimension of a high-dimensional classification problem.
Pattern Recognit., 2003

A likelihood-MPEC approach to target classification.
Math. Program., 2003

Class cover catch digraphs for latent class discovery in gene expression monitoring by DNA microarrays.
Comput. Stat. Data Anal., 2003

Classification Using Class Cover Catch Digraphs.
J. Classif., 2003

Semi-automated segmentation of cortical subvolumes via hierarchical mixture modeling.
Proceedings of the Medical Imaging 2003: Image Processing, 2003

2002
A Proof of the Spherical Homeomorphism Conjecture for Surfaces.
IEEE Trans. Medical Imaging, 2002

A Visualization Framework for the Analysis of Hyperdimensional Data.
Int. J. Image Graph., 2002

2001
Spatial Scan Density Estimates.
Technometrics, 2001

Olfactory Classification via Interpoint Distance Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2001

2000
Exact mean and mean squared error of the smoothed bootstrap mean integrated squared error estimator.
Comput. Stat., 2000

1998
Mixture structure analysis using the Akaike Information Criterion and the bootstrap.
Stat. Comput., 1998

Detection of Microcalcification Clusters in Digital Mammography Via the Spatial Scan Statistic with Stochastic Scan Partitions.
Proceedings of the Digital Mammography, 1998

1997
An analysis of local feature extraction in digital mammography.
Pattern Recognit., 1997

Segmentation of Random Fields Via Borrowed Strength Density Estimation.
IEEE Trans. Pattern Anal. Mach. Intell., 1997

1995
A PDP Approach to Localized Fractal Dimension Computation with Segmentation Boundaries.
Simul., 1995

Mammographic Computer-Assisted Diagnosis using Computational Statistics Pattern Recognition.
Real Time Imaging, 1995

1994
A qualitative analysis of the resistive grid kernel estimator.
Pattern Recognit. Lett., 1994

The detection of micro-calcifications in mammographic images using high dimensional features.
Proceedings of the Seventh Annual IEEE Symposium on Computer-Based Medical Systems (CBMS'94), 1994

1993
A self-organizing network for computing a posteriori conditional class probability.
IEEE Trans. Syst. Man Cybern., 1993

Adaptive mixture density estimation.
Pattern Recognit., 1993

1992
An initial assessment of discriminant surface complexity for power law features.
Simul., 1992

1991
Adaptive mixtures: Recursive nonparametric pattern recognition.
Pattern Recognit., 1991

1988
Temporal pattern recognition.
Proceedings of International Conference on Neural Networks (ICNN'88), 1988


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